Update documentation.

docs/examples/workflow.ipynb

@@ -36,7 +36,7 @@
  "source": [
  "## TL;DR\n",
  "\n",
- "This cell shows how build a pipeline and use it to compute a ``TimeBinned`` histogram with file type of ``FileTypeMcStas``."
+ "This cell shows how build a pipeline and use it to compute a ``TimeBinned`` histogram."
  ]
  },
  {
@@ -47,20 +47,27 @@
  "source": [
  "import sciline as sl\n",
  "from ess.nmx.workflow import collect_default_parameters, providers\n",
- "from ess.nmx.loader import InputFileName, MaximumProbability, DefaultMaximumProbability\n",
+ "from ess.nmx.loader import InputFileName, MaximumProbability, DefaultMaximumProbability, DefaultMcStasEventDataSchema, McStasEventDataSchema\n",
  "from ess.nmx.data import small_mcstas_sample\n",
  "from ess.nmx.reduction import TimeBinned, TimeBinStep, get_intervals_mcstas\n",
  "from ess.nmx.logging import get_logger as get_nmx_logger\n",
  "\n",
  "file_path = small_mcstas_sample() # Replace it with your data file path\n",
- "\n",
- "nmx_workflow = sl.Pipeline(list(providers)+[get_nmx_logger, get_intervals_mcstas],\n",
- " params={\n",
- " **collect_default_parameters(),\n",
- " MaximumProbability: DefaultMaximumProbability,\n",
- " TimeBinStep: TimeBinStep(1),\n",
- " InputFileName: InputFileName(file_path),\n",
- " })\n",
+ "mcstas_proivders = [\n",
+ " *providers,\n",
+ " get_nmx_logger, # For logging.\n",
+ " get_intervals_mcstas # Additional provider for McStas data handling.\n",
+ "]\n",
+ "mcstas_params = {\n",
+ " **collect_default_parameters(),\n",
+ " TimeBinStep: TimeBinStep(1),\n",
+ " InputFileName: InputFileName(file_path),\n",
+ " # Additional parameters for McStas data handling.\n",
+ " McStasEventDataSchema: DefaultMcStasEventDataSchema,\n",
+ " MaximumProbability: DefaultMaximumProbability,\n",
+ " }\n",
+ "\n",
+ "nmx_workflow = sl.Pipeline(mcstas_proivders, params=mcstas_params)\n",
  "\n",
  "time_binned = nmx_workflow.compute(TimeBinned)\n",
  "time_binned"